For a number of different purposes, it can be desirable to detect different types of objects in video images. Detection and/or identification of objects, and/or their locations, in video images can be challenging for computing devices (e.g., computers). Further, conventional object detection techniques used to detect and identify objects, and/or their locations, in video images can be computationally expensive. For instance, one conventional object detection technique involves exhaustively evaluating all possible object locations by sliding windows of different scales, which can be a computationally expensive computing task.